|
| Use of Meta-Analyses and Consecutive Case Reviews as a Means to Synthesize Single Case Data |
| Saturday, May 26, 2018 |
| 12:00 PM–12:50 PM |
| Manchester Grand Hyatt, Grand Hall A |
| Area: DDA/AUT; Domain: Applied Research |
| Chair: Kristina Gerencser (Marcus Autism Center) |
| CE Instructor: Kristina Gerencser, Ph.D. |
| Abstract: Within the field of applied behavior analysis, single case research designs are often used to demonstrate treatment effects. However, in order to disseminate these interventions we need larger scale analyses. The current symposium will present three papers focused on the use of meta-analyses and consecutive case reviews as models to help establish interventions as evidence-based. The first paper evaluated the procedures used in 18 previously published meta-analytic reviews on behavioral interventions for children with autism spectrum disorder. Specifically, this study evaluated the decisions rules researchers used to determine if an intervention was effective. The second paper focuses on a multi-level meta-analysis model to help establish if an intervention is effective. The authors describe this approach using two different types of differential-reinforcement-of-low-rate schedules as an example. Lastly, the third paper uses a consecutive case series analysis to evaluate outcomes related to behavioral treatment for enuresis. The evaluation and use of other models, such as these, are needed in order for the field to disseminate evidence-based interventions for individuals diagnosed with developmental disabilities. |
| Instruction Level: Intermediate |
| Keyword(s): Dissemination, Meta-analysis, Review |
| Target Audience: Researchers, clinical researchers, and other professionals in the field of behavior analysis |
| |
| Meta-Analyses of Single Case Designs in Autism Research: Current Practices and Future Directions |
| WHITNEY L. KLEINERT (May Institute), Cynthia M. Anderson (May Institute) |
| Abstract: Autism spectrum disorder (ASD) is characterized by deficits in social interaction and communication and restricted and repetitive patterns of behavior, interests, and activities. Fortunately, many interventions are available to address deficits and excesses associated with ASD and there currently are hundreds of published studies documenting such interventions. Because challenges vary by individual, single case research designs (SCD) are frequently used to examine the effectiveness of interventions. Meta-analytic procedures are a useful mechanism for synthesizing outcomes across multiple studies of a given target behavior or intervention. In this study, we identified 18 meta-analytic reviews of SCD studies conducted with individuals with ASD, and analyzed those studies to determine how decisions about effects were reached. Results indicated little agreement with regard to the ideal effect size metric and meta-analytic procedure to use. In this paper, we will (a) provide a synopsis of the current meta-analytic research on interventions targeting challenges faced by individuals with autism, and (b) offer future directions in this domain based on SCD meta-analyses in other areas. |
| |
| Multi-Level Models to Analyze Single-Case Design Data: Differential-Reinforcement-of-Low-Rate Schedules as an Example |
| JESSICA BECRAFT (Kennedy Krieger Institute), John C. Borrero (University of Maryland, Baltimore County), Shuyan Sun (University of Maryland, Baltimore County), Anlara McKenzie (University of Maryland Baltimore County, Kennedy Krieger Institute), Matthew Spann (University of Maryland, Baltimore County) |
| Abstract: Meta-analyses synthesize data across studies on a given topic. They are common tools to determine intervention effectiveness and can help to establish an intervention as evidence-based. However, most methods of conducting meta-analyses utilize between-groups design data. Techniques for meta-analyses of single-case design data as are common in behavior analysis are emerging, and multi-level models are a promising technique. The current study is an example of how to apply the multi-level model to a behavior analytic intervention. We compared two different types of differential-reinforcement-of-low-rate (DRL) schedules. DRL schedules can be used to decrease, but not eliminate target responding such as excessive hand-raising. There is some evidence that one type of DRL, the full-session DRL, may eliminate responding. We synthesized 32 published studies (187 datasets) using full-session and spaced-responding DRL schedules with humans since 1970. Furthermore, we explored potential moderators that may impact effectiveness of the interventions. Results indicated that the full-session DRL was no more likely to eliminate responding than the spaced-responding DRL. This study provides a detailed model on how to conduct a multi-level model of single-case data. To that end, future research may apply these methods to analyze other behavioral interventions. |
| |
Treatment of Enuresis for Children With Autism Spectrum Disorder |
| SHANNON KENNEDY HEWETT (Marcus Autism Center), Joanna Lomas Mevers (Marcus Autism Center), Colin S. Muething (Marcus Autism Center), Nathan Call (Marcus Autism Center), Mindy Christine Scheithauer (Marcus Autism Center) |
| Abstract: Children with developmental disabilities (DD) are more likely than typically developing peers to have issues with enuresis. Past research has shown the success of behavioral treatments consisting of scheduled sits and reinforcement for continent voids (Azrin & Fox, 1971; Leblanc, Carr, Crossett, Bennett, & Detweiler, 2005). However, this research has included small sample sizes, while studies with larger numbers have lacked key information (i.e., baseline rates and follow-up data to evaluate maintenance and generalization). The current study conducted a consecutive case series analysis of 44 individuals with developmental disabilities who completed a two-week program for enuresis. Results showed significant improvement in continent voids and follow-up data suggested positive results maintained when treatment was implemented by caregivers in a home environment. |
|
| |